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Shaurya-Shsin/
shawgpt-ft-optuna-best-3

Name: shawgpt-ft-optuna-best-3
Availability: InStock

peft

tensorboard

safetensors

generated_from_trainer

TheBloke/Mistral-7B-Instruct-v0.2-GPTQ

adapter

apache-2.0

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shawgpt-ft-optuna-best-3

This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.3107

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.00036728144071713326
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
4.5493	0.9231	3	3.7572
3.6403	1.8462	6	2.8928
2.7936	2.7692	9	2.3274
1.591	4.0	13	1.7051
1.6466	4.9231	16	1.4823
1.3941	5.8462	19	1.3940
1.2989	6.7692	22	1.3560
0.9649	8.0	26	1.3273
1.2462	8.9231	29	1.3188
1.1986	9.8462	32	1.3145
1.2022	10.7692	35	1.3127
0.8596	12.0	39	1.3112
1.1609	12.9231	42	1.3109
0.9616	13.8462	45	1.3107

Framework versions

PEFT 0.13.2
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1

Shaurya-Shsin/shawgpt-ft-optuna-best-3

shawgpt-ft-optuna-best-3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Shaurya-Shsin/
shawgpt-ft-optuna-best-3